Abstract Data-driven Anomaly Detection approaches have received increasing attention in
many application areas in the past few years as a tool to monitor complex systems in …

As technology advances, the equipment becomes more complicated, and the importance of
the Prognostics and Health Management (PHM) to monitor the condition of the equipment …

The traditional learning based static voltage stability monitoring methods require manual
labeling of a large number of training samples. Getting these labeled training sets is …

In this article, we propose an online datadriven approach that leverages the isolation
mechanism for fast event detection with low-quality data measurement. The proposed …

Monitoring the state of smart grids and detecting abnormalities are challenging tasks due to
their large size, distributed nature, and complex and stochastic dynamics. Large deployment …

This paper proposes a novel network-embedding based method to recover the missing
measurements in power systems. In particular, we first construct the spatial and temporal …

Smart grids commonly rely on analyzing sensor data to monitor power equipment. However,
these sensor data can suffer varying levels of loss or corruption due to complex …

Froth flotation is one of the most important techniques in mineral processing to beneficiate
valuable minerals from ore. As a consequence, advanced control of industrial flotation plants …

Negli ultimi dieci anni la disponibilità di grandi quantità di dati e potenza di calcolo ha spinto
la comunità scientifica verso lo sviluppo di algoritmi capaci di imparare autonomamente dai …

Smart grids being complex cyber-physical infrastructures demand real-time monitoring of
their dynamic states. Phasor measurement units (PMUs) are smart metering devices with a …